Research projects

The aim:

A successful outcome of this project will ensure that asbestos-exposed individuals are diagnosed earlier and accurately before disease symptoms manifest or progress to an advanced stage. In turn, this will facilitate the prompt implementation of treatment strategies that aim to improve the overall survival and quality of life of the patient.

Research team:

Ben Johnson, Richard Zelei, David Baker, Ling Zhuang, Emma Rath, Scott Fisher, Sonja Klebe, Anthony Linton, Yuen Yee Cheng, Elham Hosseini-Beheshti

Overview:

This project aims to identify and validate new blood-based biomarkers to facilitate an improved and less invasive diagnosis of mesothelioma. A successful outcome of this study will ensure that asbestos-exposed individuals are diagnosed earlier before disease symptoms present and/or reach an advanced stage. This in turn will facilitate a prompt administration of treatment strategies that will have a greater likelihood of improving the overall survival and quality of life of the patient.

The aim:

Given that EVs are abundantly present in biofluids, this project’s findings will help identify new biomarkers and develop less invasive, rapid, and more accessible methods for detecting Silicosis, especially for at-risk populations exposed to silica dust.

Research team:

Vivek Dharwal, Ben Johnson, Deborah Yates, Steven Kao, Anthony Linton, Elham Hosseini-Beheshti

Overview:

Silica, especially respirable crystalline silica (RCS), is recognised as a class 1 human carcinogen. Over the past two decades, the resurgence of Silicosis and silicarelated diseases has emerged as a global concern, underscoring the urgency of addressing these preventable yet fatal conditions. The health screening program
in Australia has brought forth disconcerting revelations, indicating that 20-30% of workers in the engineered stone industry bear radiological evidence of disease, marking a widespread epidemic of Silicosis within the occupational landscape.

The current method of detection of Silicosis primarily includes imaging and spirometry. However, early asymptomatic stages of the disease and limited availability of advanced imaging setup led to underdiagnosis of the disease. Thus, there is a dire need for advanced, less invasive, and rapid biomarkers to diagnose the disease. In this project, we aim to isolate EVs from the plasma samples of patients with Silicosis using the standardised method. Using the advanced omics analysis, we will extensively study EV cargo to identify biomarker signatures (proteins, miRNA, and cRNAs).

The aim:

A successful outcome of this project will facilitate the development of an EV-circRNA liquid biopsy diagnostic technique that has the potential to facilitate a sensitive and accurate diagnosis of mesothelioma.

Research team:

Ben Johnson, David Baker, Richard Zelei, Winston Lay, Tamkin Ahmadzada, Anthony Linton, Elham Hosseini-Beheshti

Overview:

Extracellular vesicles (EVs) constitute a promising liquid biopsy diagnostic biomarker due to their abundance, stability in circulation and enrichment with diseasespecific cargo. An enrichment of circular RNAs (circRNAs) in small EVs, such as exosomes, have previously been reported for a range of cancer types, thus highlighting their strong potential as biomarker for cancer diagnosis.

Therefore, Dr Ben Johnson and the project team have commenced work to assess the diagnostic accuracy and sensitivity of the eight aforementioned circRNA biomarker candidates in EVs derived from mesothelioma biospecimens. To date, the project team have effectively isolated and characterised distinct EV subpopulations (small and large EVs) derived from mesothelioma, other cancer and non-malignant cells and applied the droplet digital PCR (ddPCR) technique to quantify their associated circRNA cargo. Our data has highlighted the potential for mesothelioma-derived EVs to enable a more sensitive diagnosis of mesothelioma given that the ddPCR analysis confirmed all three distinct EV subpopulations to contain elevated circRNA levels compared to circRNAs derived from the tumour cells themselves.

Additionally, this study has demonstrated the potential for EV-derived circRNAs to facilitate a differential diagnosis of mesothelioma given that the ddPCR analysis confirmed the presence of elevated circRNA levels in EVs derived from mesothelioma cells in comparison to those from other cancer and non-malignant cell types. The next phase of the study will aim to further validate the diagnostic potential of EV-associated circRNAs using EVs isolated from patient tissue and blood samples.

The aim:

To determine whether EVs play a role in the response to Immunotherapy, how their cargo changes following treatment, and whether they can serve as predictive biomarkers for therapeutic outcomes.

Research team:

Vivek Dharwal, Tamkin Ahmadzada, Dannel Yeo, Anthony Linton, Stephen Clark, Fatemeh Vafaee, Steven Kao, Elham Hosseini-Beheshti

Overview:

Immunotherapy is a treatment that uses the body’s defence system to fight against cancer cells and has revolutionised the field of cancer therapy. In pleural mesothelioma, immunotherapies have become a standard treatment. CheckMate 743 phase 3 trial has shown that combining nivolumab plus ipilimumab (checkpoint inhibitors) significantly extended overall patient survival versus chemotherapy. However, a significant proportion of patients do not achieve a robust therapeutic response to Immunotherapy. Therefore, further research is needed to identify predictive biomarkers that could facilitate the development of personalised treatment strategies tailored to individual patient characteristics.

Extracellular vesicles (EVs), membrane-bound vesicles carrying bioactive molecules, are abundantly secreted into bodily fluids and tumour microenvironment. Their high secretion rate and emerging roles in cancers make them ideal candidates for investigation as potential predictive biomarkers in pleural mesothelioma. Dr Vivek Dharwal and the project team in this study aim to isolate and characterise extracellular vesicles from pleural mesothelioma patients undergoing Immunotherapy. Using a previously standardised protocol, EVs will be isolated from the patient’s plasma samples. The cargo of the isolated EVs, pre- and post-immunotherapy, will be comprehensively analysed using various omics platforms.

The aim:

Ultimately, we anticipate that our 3D model can be utilised as a platform for the rapid screening of new immunotherapy drug combinations that have the potential to progress to subsequent testing in clinical trials. A successful outcome will facilitate the development of improved immunotherapy combinations that can replace existing standard care treatments for mesothelioma patients. Our study will make a vital contribution towards improved mesothelioma patient survival and quality of life outcomes.

Research team:

Peter Shi, Ben Johnson, Anthony Linton, Steven Kao, Elham Hosseini-Beheshti

Overview:

Current clinical implementation of new and improved anti-cancer drug screening relies heavily on conventional two-dimensional (2D) cell culture models. As a consequence, initial anti-cancer drug tests were often found to be inefficient due to poor correlation between the 2D model and human pathophysiology. In this project, Dr Shi and the project team aim to apply a three-dimensional (3D) cell culture model to assess the anti-cancer activity of new immunotherapy drug combinations.

The research team recently developed a unique 3D model to grow mesothelioma cancer cells in combination with immune cells for immunotherapy drug screening. We expect that our 3D model closely resembles the cancer-immune cell interactions that typically occur in humans, a quality that conventional 2D models lack. We will first ensure that our proposed 3D model closely resembles the human cancer environment by comparing the composition of our 3D cell culture model to the actual mesothelioma patient tumour samples.

We will then apply this model to assess the anti-cancer activity of new immunotherapy drug combinations that are worthy of progressing to clinical trials. The immunotherapy drug combination(s) that demonstrate strong anti-cancer activity in our 3D model will then be tested in a mesothelioma mouse model (mice bearing mesothelioma tumours) and compared with the current standard care immunotherapy combination. We anticipate that the anti-cancer response to immunotherapy in the mouse model will match the drug response of cancer cells grown in our 3D model.

The aim:

Our research team aims to study changes in epigenetic biomarkers, such as microRNA and DNA methylation, in different mesothelioma patient samples that respond to pembrolizumab. The detailed clinical data available will help identify potential biomarkers that can predict how patients will response to pembrolizumab immunotherapy treatment and ultimately benefit those suffering from mesothelioma.

Research team:

Peter Shi, Helen Ke, Ling Zhuang, Emma Rath, Ben Johnson, Richard Zelei, Sakthi Priya Selvamani, Anthony Linton, Steven Kao, Yuan Yee Cheng, Elham Hosseini-Beheshti

Overview:

For many years, chemotherapy has been the primary treatment for pleural mesothelioma (PM), but it often leads to poor and short-lived responses. Recently, targeting the PD-1/PD-L1 pathway with immunecheck inhibitors has emerged as a significant treatment option for advanced non-small cell lung cancer (NSCLC) patients. While pembrolizumab, a PD-1 antibody, has shown some effectiveness in PM patients, the latest randomized clinical trial, PROMISE-Meso, did not demonstrate pembrolizumab’s superiority over chemotherapy in
terms of progression-free survival (PFS) and overall survival (OS). The over-response rate (ORR) in the PROMISE-Meso trial was similar to previous single-arm trials, suggesting that only a subgroup of PM patients may benefit from pembrolizumab. This underscores the urgent need to identify predictive biomarkers of efficacy for single-agent immunotherapy in order to identify patients likely to respond to such treatment.

So far, no research has investigated the relationship between patient response to pembrolizumab (an anti-PD-1 antibody) and epigenetic biomarkers using pleural mesothelioma patient samples.

The aim:

We strongly believe the outcome of our findings will help in the screening and developing of new drugs to enhance the survival of mesothelioma patients.

Research team:

Peter Shi, Sakthi Priya Selvamani, Richard Zelei, Ling Zhuang, Ben Johnson, Yiwei Wang, Tristan Rutland, Steven Kao, Anthony Linton, Yuen Yee Cheng, Elham Hosseini-Beheshti

Overview:

Until recently, most studies to screen drugs for cancer treatment were conducted on traditional two-dimensional (2D) models. When translated to clinical settings, these treatments failed to achieve the desired efficacy as the 2D models failed to represent the cancer environment observed in humans. Being an aggressive cancer in the thoracic region, pleural mesothelioma is presented with limited treatment options and a poor patient prognosis. A combination of chemotherapy is the first-line treatment option with a moderate response rate in patients. As the 2D models are inefficient in studying the drug resistance mechanisms observed in patients, developing a better model to understand the biology and treatment response in mesothelioma is crucial. We recently reported a 3D cell culture model for mesothelioma and used the same to understand the chemotherapy resistance mechanisms.

In this study, our research team have investigated the various biological mechanisms that confers resistance to chemotherapy by growing mesothelioma cells in 2D and 3D models. We used a combination of cisplatin and pemetrexed, the standard chemotherapy in clinics, and utilised a few other drugs in a single regimen. Our findings revealed that the mesothelioma cells grown in 3D spheroids exhibited higher resistance to cisplatin and pemetrexed combination treatment. The observed chemotherapy resistance is attributed to reduced metabolic profile, evasion of cell death, and other processes improving the survival of cancer cells. All these processes were similar in our cell culture and animal models and closely resembled the profiles of mesothelioma patients. By analysing several cancer-associated proteins, we identified key pathways that play a vital role in chemoresistance.

Research team:

Vivek Dharwal, Winston Lay, Richard Zelei, Ling Zhuang, Ali Azimi, Lucy Wang, Fatemeh Vafaee, Zaklina, Kovacevic, Steven Kao, Anthony Linton, Elham Hosseini-Beheshti

Pleural Mesothelioma (PM) is an aggressive cancer driven by the uncontrolled proliferation of mesothelial cells following asbestos exposure. The limited understanding of PM pathogenesis, the short durability of available therapies, and the high resistance rate to T cell-mediated immunotherapies underscores the urgent need for research.

Tumour microenvironment (TME) is a complex and dynamic ecosystem of cancer cells surrounded by non-malignant cells like fibroblasts, immune cells, etc. TME play a critical role in PM progression and associated drug resistance. Thus, understanding the complex signalling associated with TME can help understand PM pathogenesis and progression.

Extracellular vesicles (EVs), membrane-bound vesicles carrying bioactive molecules, are abundantly secreted into bodily fluids and TME. Their high secretion rate and emerging roles in cancers make them ideal candidates for investigation. In this project, Dr Dharwal and the team explored the role of PM-derived EVs on PM-TME to elucidate their role in modulating cellular interactions and signalling pathways. Using our established protocol, we successfully isolated three distinct EV subpopulations—2.8K, 10K, and 100K—from the conditioned media of both PM and non-malignant cells.

Using the latest omic platforms, the miRNA and protein cargo have been studied extensively. To investigate their role in TME, fibroblasts were treated with PM-derived EVs, and the expression of cancer-related genes were assessed. Through RNA sequencing and subsequent statistical enrichment analysis, followed by experimental validation in the laboratory, we identified differentially expressed genes, elucidated key molecular pathways, and highlighted potential therapeutic targets for PM.

To our knowledge, this is the first comprehensive study investigating the role of PM-derived EVs on Fibroblast and PM-TME.